Director, Safety Data Science

Description

The Safety Analytics team sits within Global Medical Safety and builds advanced analytics, AI, machine learning and data science tools that help the company make better safety decisions, run operations more effectively and reach business goals.

This is a people leader role. You will set the direction for safety analytics and AI work, lead a team, and advise senior stakeholders on strategy.

Responsibilities

• Build, check, release and refine statistical, machine learning, deep learning, natural language processing and generative AI solutions for medical safety and business needs.
• Apply advanced methods to quality monitoring, operational analytics, risk monitoring, translational analytics and strategic decisions.
• Test and adopt new technologies and methods that strengthen the team's capabilities.
• Give scientific and technical leadership across predictive safety analytics, quality monitoring and risk assessment.
• Set up fit-for-purpose data assets, pipelines, models, dashboards and applications that support data-driven decisions.
• Lead projects and teams delivering scalable analytics products, platforms and decision support tools.
• Define needs for scalable data pipelines, analytical data assets and reusable analytics products.
• Turn healthcare, safety, real-world and other enterprise data into actionable insights.
• Lead the build of analytics that improve efficiency, decisions and patient safety outcomes.
• Work with Information Technology and Digital groups on joint initiatives.
• Create dashboards, visualizations and analytics applications that show insights and support business choices.
• Give technical and analytical guidance to cross-functional partners.
• Present insights, recommendations and strategic opportunities to leadership teams.
• Contribute to scientific publications, industry collaborations, conferences and external engagements.
• Lead strategic initiatives of growing complexity and impact.
• Coach and develop analytics staff while building a culture of innovation, teamwork and continuous learning.
• Drive organization-wide adoption of new analytical capabilities and practices.

Requirements

• An advanced degree in Statistics, Biostatistics, Data Science, Computer Science, Mathematics, Bioinformatics, Biomedical Informatics, Epidemiology or a related quantitative field. A PhD is preferred; a Master's degree with significant relevant experience is considered.
• Significant experience leading work in advanced analytics, machine learning, AI, data science, healthcare analytics, medical safety analytics or related scientific areas.
• Experience supporting medical safety, pharmacovigilance, real-world evidence, healthcare analytics or related life-science functions is required.
• Proven ability to lead analytics, AI/ML or quantitative scientific initiatives.
• Proven ability to build end-to-end analytical solutions, from data acquisition through deployment and business adoption.
• Proven ability to turn analytical concepts into scalable, production-grade solutions that deliver measurable business value.
• Proven ability to lead projects, teams and cross-functional initiatives.
• Experience with healthcare, safety, real-world or enterprise-scale data environments is preferred.
• Experience presenting scientific work to both technical and non-technical audiences is required.
• Proficiency in Python, R and SQL.
• Expertise in statistical methods, predictive modeling, machine learning, deep learning, generative AI and large language models.
• Understanding of cloud-based analytical architectures.
• Experience deploying AI/ML solutions using modern MLOps, CI/CD and model lifecycle management practices.
• Understanding of data engineering, feature engineering and scalable analytical architectures.
• Understanding of regulatory expectations, validation principles, governance requirements and responsible AI practices.
• Strong analytical, problem-solving, communication and stakeholder management skills.
• Ability to connect business strategy, scientific methodology and technical implementation to create organizational impact.
• Preferred skills: advanced analytics, budget management, compliance management, critical thinking, data analysis, data privacy standards, data quality, data reporting, data savvy, data science, data visualization, developing others, digital fluency, inclusive leadership, leadership, program management, strategic thinking and succession planning.

Conditions

Hybrid work model.

Locations are Horsham, Pennsylvania and Titusville, New Jersey, United States.

The anticipated base pay range is $164,000 - $282,900.

Accommodations are available for applicants with disabilities during the interview process.

Benefits

• Eligible for the company's consolidated retirement plan (pension) and savings plan (401(k)), subject to plan terms.
• Eligible for the long-term incentive program.
• Vacation: 120 hours per calendar year.
• Sick time: 40 hours per calendar year, or 48 hours for Colorado residents, or 56 hours for Washington residents.
• Holiday pay, including floating holidays: 13 days per calendar year.
• Work, personal and family time: up to 40 hours per calendar year.
• Parental leave: 480 hours within one year of the birth, adoption or foster care of a child.
• Bereavement leave: 240 hours for an immediate family member and 40 hours for an extended family member per calendar year.
• Caregiver leave: 80 hours in a 52-week rolling period, listed alongside 10 days.
• Volunteer leave: 32 hours per calendar year.
• Military spouse time off: 80 hours per calendar year.
• Time off eligibility depends on policies and date of hire.